OpenMebius2: GUI-based software for 13C-metabolic flux analysis with tracer labeling pattern suggestions for precise...

Area of Science:

• Metabolic Engineering
• Systems Biology
• Biotechnology

Background:

• ¹³C-metabolic flux analysis (¹³C-MFA) is essential for understanding cellular metabolism.
• Accurate flux determination relies heavily on optimal tracer labeling patterns.
• Optimizing these patterns is a significant experimental challenge.

Purpose of the Study:

• To address the challenge of optimizing tracer labeling patterns for ¹³C-MFA.
• To introduce OpenMebius2, an integrated software platform for ¹³C-MFA.
• To provide a function within OpenMebius2 that suggests optimal tracer labeling patterns.

Main Methods:

• Development of OpenMebius2, a graphical user interface (GUI)-based software.
• Integration of a tracer labeling pattern suggestion function into the software.
• Application of the software to support experimental design in ¹³C-MFA.

Main Results:

• Successful development of the OpenMebius2 integrated platform.
• Implementation of a novel function for suggesting ¹³C-MFA tracer labeling patterns.
• Enhanced support for experimental design and optimization in metabolic flux studies.

Conclusions:

• OpenMebius2 provides a user-friendly solution for ¹³C-MFA.
• The integrated tracer labeling pattern suggestion function aids in improving experimental precision.
• This tool facilitates more accurate metabolic flux distribution determination.